Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/13290
Title: EmoSnaps: a mobile application for emotion recall from facial expressions
Authors: Niforatos, Evangelos 
Karapanos, Evangelos 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Keywords: Day Reconstruction Method (DRM);Emotion self-reporting;Experience reconstruction;Experience Sampling Method (ESM);User experience (UX) evaluation
Issue Date: Feb-2015
Source: Personal and Ubiquitous Computing, 2015, vol. 19, no. 2, pp. 425–444.
Volume: 19
Issue: 2
Start page: 425
End page: 444
Journal: Personal and Ubiquitous Computing 
Abstract: We introduce EmoSnaps, a mobile application that captures unobtrusively pictures of one’s facial expressions throughout the day and uses them for later recall of her momentary emotions. We describe two field studies that employ EmoSnaps in an attempt to investigate if and how individuals and their relevant others infer emotions from self-face and familiar face pictures, respectively. Study 1 contrasted users’ recalled emotions as inferred from EmoSnaps’ self-face pictures to ground truth data as derived from Experience Sampling. Contrary to our expectations, we found that people are better able to infer their past emotions from a self-face picture the longer the time has elapsed since capture. Study 2 assessed EmoSnaps’ ability to capture users’ experiences while interacting with different mobile apps. The study revealed systematic variations in users’ emotions while interacting with different categories of mobile apps (such as productivity and entertainment), social networking services, as well as direct social communications through phone calls and instant messaging, but also diurnal and weekly patterns of happiness as inferred from EmoSnaps’ self-face pictures. All in all, the results of both studies provided us with confidence over the validity of self-face pictures captured through EmoSnaps as memory cues for emotion recall, and the effectiveness of the EmoSnaps tool in measuring users’ momentary experiences.
ISSN: 16174917
DOI: 10.1007/s00779-014-0777-0
Rights: © Springer
Attribution-NonCommercial-NoDerivs 3.0 United States
Type: Article
Affiliation : University of Lugano 
Madeira Interactive Technologies Institute 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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